{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 公募基金组合"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 本段代码利用quantOS系统进行公募股票和债券基金收益率分析及组合构建，比较了等权重和波动率倒数加权法两种组合构建方法"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 系统设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# encoding: utf-8\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "import seaborn as sns\n",
    "import matplotlib.mlab as mlab\n",
    "import scipy.stats as stats\n",
    "from matplotlib.ticker import Formatter\n",
    "\n",
    "sns.set_style('darkgrid')\n",
    "sns.set_context('poster')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from jaqs.data import RemoteDataService, DataApi\n",
    "import jaqs.util as jutil\n",
    "from __future__ import print_function, unicode_literals, division, absolute_import\n",
    "\n",
    "from jaqs.data import RemoteDataService, DataView"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Begin: DataApi login 17321165656@tcp://data.quantos.org:8910\n",
      "    login success \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0,'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataview_dir_path = '.'\n",
    "backtest_result_dir_path = '.'\n",
    "\n",
    "import os\n",
    "phone = os.environ.get('QUANTOS_USER')\n",
    "token = os.environ.get('QUANTOS_TOKEN')\n",
    "\n",
    "data_config = {\n",
    "  \"remote.data.address\": \"tcp://data.quantos.org:8910\",\n",
    "  \"remote.data.username\": phone,\n",
    "  \"timeout\": 3600,\n",
    "  \"remote.data.password\": token\n",
    "}\n",
    "\n",
    "api_uat = DataApi(addr='tcp://data.quantos.org:8910')\n",
    "api_uat.login(phone, token)\n",
    "\n",
    "ds = RemoteDataService()\n",
    "ds.init_from_config(data_config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 设置参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "START_DATE, END_DATE = 20160101, 20180511"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 从数据库中取出符合条件的基金"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fundlist(api, invest_type, invest_style,launch_date):\n",
    "    df, msg = api.query(\n",
    "            view = 'lb.mfInfo',\n",
    "            fields = 'invest_type,invest_style,status',\n",
    "            filter = \"\",\n",
    "            data_format = 'pandas'\n",
    "    )\n",
    "    df = df[(df['invest_type'] == invest_type)\n",
    "           & (df['status'] == 101001000)\n",
    "           & (df['invest_style'] == invest_style)\n",
    "           & (df['setup_date'] < launch_date)]\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 取出基金历史净值和指数的历史价格信息，注意需要用复权因子校正后的净值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fundnav(api, symbol, start_date, end_date):\n",
    "    df, msg = api.query(\n",
    "            view = 'lb.mfNav',\n",
    "            fields = 'price_date,nav_adjusted',\n",
    "            filter = 'start_pdate=' + str(start_date) + '&end_pdate=' + str(end_date) + '&symbol=' + symbol,\n",
    "            data_format = 'pandas'\n",
    "    )\n",
    "    \n",
    "    if df is None:\n",
    "        print(df, msg)\n",
    "    df.index = df['price_date'].astype(np.integer)\n",
    "    df.sort_index(inplace = True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每只基金的表现，包括return，volatility，sharpe ratio，beta，最大回撤等"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cal_return(api, symbol, start, end):\n",
    "\n",
    "    df_nav = get_fundnav(api, symbol, start, end)\n",
    "    if len(df_nav) == 0:\n",
    "        return None, None, None\n",
    "    strategy_value = pd.DataFrame(df_nav['nav_accumulated']).fillna(method = 'ffill')\n",
    "    strategy_value.columns = ['strat']\n",
    "    df_returns = strategy_value.pct_change(periods = 1).fillna(0.0)\n",
    "    df_returns = df_returns.join((df_returns.loc[:, ['strat']] + 1.0).cumprod(), rsuffix = '_cum')\n",
    "\n",
    "    start = pd.to_datetime(start, format = '%Y%m%d')\n",
    "    end   = pd.to_datetime(end, format = '%Y%m%d')\n",
    "    years = (end - start).days / 365.0\n",
    "\n",
    "    strat_cum = df_returns['strat_cum'].values\n",
    "\n",
    "#     max_dd_end = np.argmax(np.maximum.accumulate(strat_cum) - strat_cum)   # end of the period\n",
    "#     max_dd_start   = np.argmax(strat_cum[:max_dd_end])\n",
    "#     max_dd = (strat_cum[max_dd_start] - strat_cum[max_dd_end])/strat_cum[max_dd_end]\n",
    "\n",
    "    # 计算收益率相关指标\n",
    "    performance_metrics = dict()\n",
    "\n",
    "    performance_metrics['Annual Return (%)'] =\\\n",
    "        100 * (np.power(df_returns.loc[:, 'strat_cum'].values[-1], 1./years) - 1)\n",
    "    performance_metrics['Annual volatility (%)'] =\\\n",
    "        100 * (df_returns.loc[:, 'strat'].std() * np.sqrt(242))\n",
    "    performance_metrics['Sharpe Ratio'] = (performance_metrics['Annual Return (%)']/performance_metrics['Annual volatility (%)'])\n",
    "\n",
    "    # 计算风险相关指标\n",
    "    risk_metrics = dict()\n",
    "#     risk_metrics['Maximum Drawdown (%)'] = max_dd * 100\n",
    "#     risk_metrics['Maximum Drawdown Start'] = df_returns.index[max_dd_end]\n",
    "#     risk_metrics['Maximum Drawdown End'] = df_returns.index[max_dd_start]\n",
    "    \n",
    "    output_returns = df_returns.copy()\n",
    "    output_returns['symbol'] = symbol\n",
    "    output_returns = output_returns.reset_index()\n",
    "    output_returns.columns = ['trade_date', 'strat','strat_cum','symbol']\n",
    "    \n",
    "    return performance_metrics, risk_metrics, output_returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将上述函数按流程组织在一起，计算出所有符合条件基金的表现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 剔除指数型基金以及2018年1月1日后发行的股票和债券基金，债券基金选择发行规模最大的1000支作为研究对象\n",
    "df = get_fundlist(api_uat, '股票型', '股票型', str(20180101))\n",
    "df_bond = get_fundlist(api_uat, '债券型', '债券型', str(20180101))\n",
    "df_bond = df_bond.sort_values('issue_totals', ascending = False).head(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbols = df['symbol'].values.tolist()\n",
    "symbols_bond = df_bond['symbol'].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "indicators = list()\n",
    "indicators_bond = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_returns = pd.DataFrame()\n",
    "daily_returns_bond = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for symbol in symbols:\n",
    "    performance_metrics, risk_metrics, output_returns = cal_return(api_uat, symbol, START_DATE, END_DATE)\n",
    "    \n",
    "    if performance_metrics is None:\n",
    "        continue\n",
    "    daily_returns = pd.concat([daily_returns, output_returns], axis = 0)\n",
    "    indicators.append((symbol,\n",
    "                      performance_metrics['Annual Return (%)'],\n",
    "                      performance_metrics['Annual volatility (%)'],\n",
    "                      performance_metrics['Sharpe Ratio'],\n",
    "                      output_returns['strat_cum'].iat[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for symbol in symbols_bond:\n",
    "    performance_metrics, risk_metrics, output_returns = cal_return(api_uat, symbol, START_DATE, END_DATE)\n",
    "    \n",
    "    if performance_metrics is None:\n",
    "        continue\n",
    "    daily_returns_bond = pd.concat([daily_returns_bond, output_returns], axis = 0)\n",
    "    indicators_bond.append((symbol,\n",
    "                      performance_metrics['Annual Return (%)'],\n",
    "                      performance_metrics['Annual volatility (%)'],\n",
    "                      performance_metrics['Sharpe Ratio'],\n",
    "                      output_returns['strat_cum'].iat[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = ['symbol', 'AnnualReturn', 'AnnualVolatility', 'SharpeRatio', 'StratCumReturn']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股票基金收益率描述统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AnnualReturn</th>\n",
       "      <th>AnnualVolatility</th>\n",
       "      <th>SharpeRatio</th>\n",
       "      <th>StratCumReturn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>307.000000</td>\n",
       "      <td>307.000000</td>\n",
       "      <td>307.000000</td>\n",
       "      <td>307.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.364186</td>\n",
       "      <td>18.482186</td>\n",
       "      <td>0.303119</td>\n",
       "      <td>1.118137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.636670</td>\n",
       "      <td>4.854557</td>\n",
       "      <td>0.639726</td>\n",
       "      <td>0.219610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-21.810494</td>\n",
       "      <td>0.386981</td>\n",
       "      <td>-0.902726</td>\n",
       "      <td>0.559690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-1.415731</td>\n",
       "      <td>15.445819</td>\n",
       "      <td>-0.078384</td>\n",
       "      <td>0.966925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.587610</td>\n",
       "      <td>19.102425</td>\n",
       "      <td>0.206999</td>\n",
       "      <td>1.086700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>10.078499</td>\n",
       "      <td>21.538705</td>\n",
       "      <td>0.616507</td>\n",
       "      <td>1.254229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>30.874093</td>\n",
       "      <td>39.064090</td>\n",
       "      <td>7.204041</td>\n",
       "      <td>1.886456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AnnualReturn  AnnualVolatility  SharpeRatio  StratCumReturn\n",
       "count    307.000000        307.000000   307.000000      307.000000\n",
       "mean       4.364186         18.482186     0.303119        1.118137\n",
       "std        8.636670          4.854557     0.639726        0.219610\n",
       "min      -21.810494          0.386981    -0.902726        0.559690\n",
       "25%       -1.415731         15.445819    -0.078384        0.966925\n",
       "50%        3.587610         19.102425     0.206999        1.086700\n",
       "75%       10.078499         21.538705     0.616507        1.254229\n",
       "max       30.874093         39.064090     7.204041        1.886456"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_returns = pd.DataFrame.from_records(indicators, columns = labels)\n",
    "df_returns.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_returns = pd.merge(left = df_returns, right = df[['symbol', 'issue_totals']], how = 'left', on = 'symbol')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股票基金年化收益率分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1290fdd8>"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x13071550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画日对数收益率分布直方图\n",
    "fig = plt.figure(figsize=(18, 18))\n",
    "v = df_returns['AnnualReturn'].dropna().values\n",
    "avgRet = np.mean(v)\n",
    "stdRet = np.std(v)\n",
    "x = np.linspace(avgRet - 3*stdRet, avgRet + 3*stdRet, 100)\n",
    "y = mlab.normpdf(x, avgRet, stdRet)\n",
    "kde = stats.gaussian_kde(v)\n",
    "\n",
    "# plot the histogram\n",
    "plt.subplot(211)\n",
    "plt.hist(v, 50, weights = np.ones(len(v))/len(v), alpha = 0.4)\n",
    "plt.axvline(x = avgRet, color = 'red', linestyle = '--', linewidth = 0.8, label = 'Mean Value')\n",
    "plt.axvline(x = avgRet - 2 * stdRet, color = 'blue', linestyle = '--', linewidth = 0.8, label = '-2 Standard Deviation')\n",
    "plt.axvline(x = avgRet + 2 * stdRet, color = 'blue', linestyle = '--', linewidth = 0.8, label = '2 Standard Deviation')\n",
    "plt.ylabel('Percentage', fontsize = 10)\n",
    "plt.legend(fontsize = 10)\n",
    "\n",
    "# plot the kde and normal fit\n",
    "plt.subplot(212)\n",
    "plt.plot(x, kde(x), label = 'Kernel Density Estimation')\n",
    "plt.plot(x, y, color = 'black', linewidth=1, label = 'Normal Fit')\n",
    "plt.ylabel('Probability', fontsize = 10)\n",
    "plt.axvline(x = avgRet, color = 'red', linestyle = '--', linewidth = 0.8, label = 'Mean Count')\n",
    "plt.legend(fontsize = 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 债券基金收益率描述统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AnnualReturn</th>\n",
       "      <th>AnnualVolatility</th>\n",
       "      <th>SharpeRatio</th>\n",
       "      <th>StratCumReturn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>998.000000</td>\n",
       "      <td>998.000000</td>\n",
       "      <td>998.000000</td>\n",
       "      <td>998.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.416466</td>\n",
       "      <td>2.560495</td>\n",
       "      <td>1.284039</td>\n",
       "      <td>1.034567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.282857</td>\n",
       "      <td>2.557381</td>\n",
       "      <td>1.541210</td>\n",
       "      <td>0.052420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-20.272923</td>\n",
       "      <td>0.194170</td>\n",
       "      <td>-1.540819</td>\n",
       "      <td>0.586000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.880961</td>\n",
       "      <td>1.092701</td>\n",
       "      <td>0.361577</td>\n",
       "      <td>1.020906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.718000</td>\n",
       "      <td>1.771565</td>\n",
       "      <td>0.960840</td>\n",
       "      <td>1.041000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.469773</td>\n",
       "      <td>3.171727</td>\n",
       "      <td>1.872507</td>\n",
       "      <td>1.059240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.288286</td>\n",
       "      <td>32.461291</td>\n",
       "      <td>20.173094</td>\n",
       "      <td>1.342200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       AnnualReturn  AnnualVolatility  SharpeRatio  StratCumReturn\n",
       "count    998.000000        998.000000   998.000000      998.000000\n",
       "mean       1.416466          2.560495     1.284039        1.034567\n",
       "std        2.282857          2.557381     1.541210        0.052420\n",
       "min      -20.272923          0.194170    -1.540819        0.586000\n",
       "25%        0.880961          1.092701     0.361577        1.020906\n",
       "50%        1.718000          1.771565     0.960840        1.041000\n",
       "75%        2.469773          3.171727     1.872507        1.059240\n",
       "max       13.288286         32.461291    20.173094        1.342200"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_returns_bond = pd.DataFrame.from_records(indicators_bond, columns = labels)\n",
    "df_returns_bond.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_returns_bond = pd.merge(left = df_returns_bond, right = df_bond[['symbol', 'issue_totals']], how = 'left', on = 'symbol')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 债券基金年化收益率分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12f20470>"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x127a3860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 画日对数收益率分布直方图\n",
    "fig = plt.figure(figsize=(18, 18))\n",
    "v = df_returns_bond['AnnualReturn'].dropna().values\n",
    "avgRet = np.mean(v)\n",
    "stdRet = np.std(v)\n",
    "x = np.linspace(avgRet - 3*stdRet, avgRet + 3*stdRet, 100)\n",
    "y = mlab.normpdf(x, avgRet, stdRet)\n",
    "kde = stats.gaussian_kde(v)\n",
    "\n",
    "# plot the histogram\n",
    "plt.subplot(211)\n",
    "plt.hist(v, 50, weights = np.ones(len(v))/len(v), alpha = 0.4)\n",
    "plt.axvline(x = avgRet, color = 'red', linestyle = '--', linewidth = 0.8, label = 'Mean Value')\n",
    "plt.axvline(x = avgRet - 2 * stdRet, color = 'blue', linestyle = '--', linewidth = 0.8, label = '-2 Standard Deviation')\n",
    "plt.axvline(x = avgRet + 2 * stdRet, color = 'blue', linestyle = '--', linewidth = 0.8, label = '2 Standard Deviation')\n",
    "plt.ylabel('Percentage', fontsize = 10)\n",
    "plt.legend(fontsize = 10)\n",
    "\n",
    "# plot the kde and normal fit\n",
    "plt.subplot(212)\n",
    "plt.plot(x, kde(x), label = 'Kernel Density Estimation')\n",
    "plt.plot(x, y, color = 'black', linewidth=1, label = 'Normal Fit')\n",
    "plt.ylabel('Probability', fontsize = 10)\n",
    "plt.axvline(x = avgRet, color = 'red', linestyle = '--', linewidth = 0.8, label = 'Mean Count')\n",
    "plt.legend(fontsize = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns_bond = daily_returns_bond.pivot_table(index = 'trade_date', columns = 'symbol', values = 'strat')\n",
    "df_daily_returns_bond = df_daily_returns_bond.fillna(0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns = daily_returns.pivot_table(index = 'trade_date', columns = 'symbol', values = 'strat')\n",
    "df_daily_returns = df_daily_returns.fillna(0.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 比较同一股票基金在不同年份的表现，检验是否有持续性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns_2016 = df_daily_returns.loc[:20170101]\n",
    "df_daily_returns_2017 = df_daily_returns.loc[20170101:20180101]\n",
    "df_daily_returns_2018 = df_daily_returns.loc[20180101:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns_2016_cum = pd.DataFrame((df_daily_returns_2016 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_2016_cum.columns = ['2016rank']\n",
    "df_daily_returns_2017_cum = pd.DataFrame((df_daily_returns_2017 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_2017_cum.columns = ['2017rank']\n",
    "df_daily_returns_2018_cum = pd.DataFrame((df_daily_returns_2018 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_2018_cum.columns = ['2018rank']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_rank = pd.concat([df_daily_returns_2016_cum, df_daily_returns_2017_cum, df_daily_returns_2018_cum], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2016rank</th>\n",
       "      <th>2017rank</th>\n",
       "      <th>2018rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016rank</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.082479</td>\n",
       "      <td>0.144213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017rank</th>\n",
       "      <td>0.082479</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018rank</th>\n",
       "      <td>0.144213</td>\n",
       "      <td>0.011841</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          2016rank  2017rank  2018rank\n",
       "2016rank  1.000000  0.082479  0.144213\n",
       "2017rank  0.082479  1.000000  0.011841\n",
       "2018rank  0.144213  0.011841  1.000000"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rank.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 比较同一债券基金在不同年份的表现，检验是否有持续性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns_bond_2016 = df_daily_returns_bond.loc[:20170101]\n",
    "df_daily_returns_bond_2017 = df_daily_returns_bond.loc[20170101:20180101]\n",
    "df_daily_returns_bond_2018 = df_daily_returns_bond.loc[20180101:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_daily_returns_bond_2016_cum = pd.DataFrame((df_daily_returns_bond_2016 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_bond_2016_cum.columns = ['2016rank']\n",
    "df_daily_returns_bond_2017_cum = pd.DataFrame((df_daily_returns_bond_2017 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_bond_2017_cum.columns = ['2017rank']\n",
    "df_daily_returns_bond_2018_cum = pd.DataFrame((df_daily_returns_bond_2018 + 1).cumprod().iloc[-1, :].rank(ascending = False))\n",
    "df_daily_returns_bond_2018_cum.columns = ['2018rank']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_rank_bond = pd.concat([df_daily_returns_bond_2016_cum, df_daily_returns_bond_2017_cum, df_daily_returns_bond_2018_cum], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2016rank</th>\n",
       "      <th>2017rank</th>\n",
       "      <th>2018rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016rank</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.148519</td>\n",
       "      <td>-0.023175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017rank</th>\n",
       "      <td>0.148519</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.047603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018rank</th>\n",
       "      <td>-0.023175</td>\n",
       "      <td>-0.047603</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          2016rank  2017rank  2018rank\n",
       "2016rank  1.000000  0.148519 -0.023175\n",
       "2017rank  0.148519  1.000000 -0.047603\n",
       "2018rank -0.023175 -0.047603  1.000000"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rank_bond.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 挑选出在2016年表现最好的三支股票基金和债券基金构建组合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_fund = df_daily_returns_2016_cum.sort_values('2016rank').index[:3].values.tolist()\n",
    "bond_fund = df_daily_returns_bond_2016_cum.sort_values('2016rank').index[:3].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_ret_stock = df_daily_returns[stock_fund]\n",
    "daily_ret_bond = df_daily_returns_bond[bond_fund]\n",
    "daily_ret_all = pd.concat([daily_ret_stock, daily_ret_bond], axis = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 等权重组合基金"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ew = pd.DataFrame(daily_ret_all.mean(axis = 1))\n",
    "df_ew.columns = ['daily_ew_ret']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Annual Return is: 0.1026\n",
      "Annual Volatility is: 0.0664\n",
      "Sharpe Ratio is: 1.5452\n"
     ]
    }
   ],
   "source": [
    "print('Annual Return is: %.4f' % (df_ew.mean() * 242))\n",
    "print('Annual Volatility is: %.4f' % (df_ew.std() * np.sqrt(242)))\n",
    "print('Sharpe Ratio is: %.4f' % (df_ew.mean()/df_ew.std() * np.sqrt(242)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 根据波动率倒数组合基金"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\lli\\AppData\\Local\\QuantosFinanceTerminal\\python\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: pd.rolling_std is deprecated for DataFrame and will be removed in a future version, replace with \n",
      "\tDataFrame.rolling(window=30,center=False).std()\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "# 计算各支基金过去30个交易日波动率\n",
    "df_volatility = pd.rolling_std(daily_ret_all, 30)\n",
    "df_volatility = df_volatility.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 根据波动率确定各支基金在组合中的权重\n",
    "df_inverse_volatility = 1.0/df_volatility\n",
    "df_inverse_volatility = df_inverse_volatility.replace(np.inf, 0.0)\n",
    "df_weight = df_inverse_volatility.divide(df_inverse_volatility.sum(axis = 1), axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 根据权重组合各支基金\n",
    "df_rp = pd.DataFrame(df_daily_returns.loc[df_weight.index].mul(df_weight).sum(axis = 1))\n",
    "df_rp.columns = ['daily_rp_ret']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Annual Return is: 0.0242\n",
      "Annual Volatility is: 0.0194\n",
      "Sharpe Ratio is: 1.2487\n"
     ]
    }
   ],
   "source": [
    "print('Annual Return is: %.4f' % (df_rp.mean() * 242))\n",
    "print('Annual Volatility is: %.4f' % (df_rp.std() * np.sqrt(242)))\n",
    "print('Sharpe Ratio is: %.4f' % (df_rp.mean()/df_rp.std() * np.sqrt(242)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyFormatter(Formatter):\n",
    "    def __init__(self, dates, fmt='%Y%m'):\n",
    "        self.dates = dates\n",
    "        self.fmt = fmt\n",
    "\n",
    "    def __call__(self, x, pos=0):\n",
    "        \"\"\"Return the label for time x at position pos\"\"\"\n",
    "        ind = int(np.round(x))\n",
    "        if ind >= len(self.dates) or ind < 0:\n",
    "            return ''\n",
    "\n",
    "        # return self.dates[ind].strftime(self.fmt)\n",
    "        return pd.to_datetime(self.dates[ind], format=\"%Y%m%d\").strftime(self.fmt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_ret_compare = pd.concat([df_ew, df_rp], axis = 1)\n",
    "df_ret_compare = df_ret_compare.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cum_ret_compare = (df_ret_compare + 1).cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x125324a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(1, 1, figsize=(21, 10))\n",
    "\n",
    "idx0 = df_cum_ret_compare.index\n",
    "idx = range(len(idx0))\n",
    "\n",
    "# ax1.plot(idx, df_cum_ret_compare.daily_issue_ret, lw=1.5, color='indianred', label='Issue value weight')\n",
    "ax1.plot(idx, df_cum_ret_compare.daily_ew_ret, lw=1.5, color='royalblue', label='Equal weight')\n",
    "ax1.plot(idx, df_cum_ret_compare.daily_rp_ret, lw=1.5, color='purple', label='Reverse volatility weight')\n",
    "\n",
    "# ax1.axhline(0.0, color='k', lw=0.5, ls='--')\n",
    "\n",
    "ax1.legend(loc='upper left')\n",
    "ax1.set_xlabel(\"Date\")\n",
    "ax1.set_ylabel(\"Return\")\n",
    "ax1.xaxis.set_major_formatter(MyFormatter(idx0, '%Y%m%d'))\n",
    "\n",
    "plt.tight_layout()\n",
    "# fig.savefig('lgt_brinson_cum.png')\n",
    "# plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 注解：\n",
    "## 1. 债券基金在2017年表现较差，而股票基金表现更好\n",
    "## 2. 第二种根据波动率倒数的加权方式更倾向于债券基金，所以在样本内表现不如等权重组合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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